This study identifies very small businesses (VSBs) as survival-oriented entrepreneurs. Using a unique survey of 1450 VSB owners (with fewer than 50 employees) across China, combined with regional fiscal and institutional data, we provide the first micro-level evidence on how VSBs allocate entrepreneurial efforts to enhance survival in a rent-seeking society.We classify VSBs along three dimensions: whether they are subject to governmental apportion, operate in new technological industries, or possess political connections. Our findings reveal that VSBs generally relinquish attempts to win rent-seeking contests or resist rent extraction. With the exception of those in new technological sectors, VSBs increase productive—but not unproductive—activities, benefiting from spillover effects generated by rent-seeking among larger firms. VSBs not subject to government apportion reduce rent- seeking efforts when rent-seeking opportunities expand. Finally, politically connected VSBs do not adjust their entrepreneurial efforts in response to institutional improvements but increase innovation after property rights are secured through government ties. In summary, a rent-seeking society presents both opportunities and obstacles for VSBs, including those without political connections.

As a new form of urban transportation, dockless bike sharing effectively improves connectivity between work and residence through its spatial penetration capabilities, reshaping commuting patterns and travel efficiency for workers. Whether the widespread adoption of dockless bike sharing has a positive impact on the labor market warrants further investigation. This paper uses the entry of the dockless bike sharing platform as a quasi-natural experiment, examining its impact on wages for short-distance commuters and the underlying mechanisms through micro-level individual data. This paper finds that the widespread adoption of bike sharing significantly increases workers’ wage levels, a conclusion that remains valid after a series of robustness tests. The mechanism behind this lies in the fact that bike sharing reduces commuting time and frees up additional working hours, thereby promoting wage growth by improving workers’ time allocation. Heterogeneity analysis indicates that bike sharing has a greater wage premium effect on urban vulnerable groups, outdoor mobile office workers, and short-distance workers, and the effect is more pronounced in cities with high levels of urban sprawl. This paper deepens the understanding of how dockless bike sharing enhances the welfare of urban workers, providing empirical evidence and decision-making references for governments to improve the new form of urban transportation and labor market development.

As an increasingly frequent external uncertainty shock, the impact of extreme weather shocks on the labor market has been extensively discussed, whereas few studies have examined the consequences from the perspective of the employment structure. Focusing on the employment structure of enterprises, this study utilizes the data of World Bank Enterprise Survey in China (2024) and analyzes the employment strategies adopted by enterprises in the face of extreme weather shocks. Empirical evidence indicates that under extreme weather shocks, the practices of non-standard employment (NSE) among enterprises have increased significantly. To better explain this observation, the study provides suggestive evidence for two potential channels of production interruptions and capacity underutilization. Specifically, extreme weather shocks tend to contribute to production disruptions and idle capacity, which may subsequently incentivize enterprises to adopt adaptive behaviors of increasing NSE to reduce costs and enhance operational flexibility. Further analysis reveals significant heterogeneity in the impact of extreme weather shocks, with more pronounced effects observed among small and medium-sized, low labor-regulated, low-reputation, and non-exporting firms. Finally, NSE practices adopted by enterprises in response to extreme weather shocks are found to come at the expense of employment stability and human capital accumulation. This study offers a novel perspective on NSE practices and provides new insights for climate policy formulation.

The accelerating pace of population aging has spurred governments worldwide to proactively tap into the potential of the elderly labor market. Policies such as raising the statutory retirement age and advancing the “silver dividend” initiative aim to convert demographic shifts into economic dividends. Meanwhile, artificial intelligence (AI) is rapidly reshaping the nature of the labor market. Existing research has largely focused on the determinants of retirement decisions or the labor market effects of AI, with relatively little attention paid to the delayed retirement behavior of older workers in the era of AI. Against this backdrop, this paper explores the impact of AI exposure on older workers' decisions to delay retirement and the underlying mechanisms. Using micro-level individual data from China, this paper finds that the higher the level of AI exposure in an older worker's occupation, the lower the probability of delaying retirement. Mechanism tests reveal that exposure to AI reduces older workers' probability of delayed retirement by leading to job displacement, a decline in work-related returns, and a loss of confidence in the future. Furthermore, it is found that the negative impact of AI exposure on delayed retirement is more pronounced in groups that are highly educated, male, in poor health, have high family income, have purchased pension insurance, and receive support from their children. This paper offers insights and policy recommendations on how to better tap into the potential of the older workforce in the age of AI.

Based on data from the China Labor Dynamics Survey for 2012, 2014, and 2016, combined with city-level data on the density of robot installations, this paper examines the impact of robot applications on individual labor market entry and exit decisions. The empirical results show that (1) for every 10% rise in robot application, an individual's labor force participation rate significantly increases by 2.31%, and the finding remains robust after a series of tests. (2) Mechanistic analyses show that robot application contribute to increasing employment, facilitating skills upgrading and matching, improving work conditions, optimizing worker status, and thus increasing individual workforce participation. (3) Heterogeneity analysis shows that the impact of robot application varies across different groups, with more significant effects on labor force participation for women, young and middle-aged people, individuals with good health, and individuals with low and high skills. Based on research findings, this paper suggests that China can unleash the potential labor force by promoting the development of robot application to alleviate the labor shortage caused by population aging and childlessness. At the same time, the government also needs to preempt the problem of unequal labor participation that may be triggered by the application of robots and promote the fair and healthy development of the labor market.

Urbanization often exacerbates regional inequality while promoting economic growth. How to effectively coordinate spatial expansion and inclusive growth has become a policy challenge for developing economies. To address institutional constraints inherent in traditional urbanization pathways, China launched a new-type urbanization reform in 2014, aiming to achieve inclusive development within the region through urban residency conversion and equalization of public services. Exploiting the staggered rollout of this reform as a quasi-natural experiment and combining it with township-level nighttime-light data, we estimate a staggered difference-in-differences model that isolates the policy's effect on intra-county inequality. The results show that the reform significantly narrows economic disparities within counties. Mechanism analyses indicate that the policy raises factor mobility and spatial connectivity by expanding off-farm employment, attracting non-agricultural firms, and upgrading transport and communication infrastructure, thereby compressing within-county inequality. Spatially, the reform widens the gap between pilot and non-pilot counties while fostering convergence inside treated counties, with the largest gains accruing to the most disadvantaged townships. Heterogeneity analyses show that the policy has a more significant effect in counties with lower initial inequality, lighter fiscal pressure, higher population density, and stronger public-service provision. These findings provide new evidence on how institutional urbanization reforms can advance inclusive regional development.

The development of the rural digital economy has significantly enhanced local competitiveness and reshaped migration patterns in China’s rural areas. Using LandScan data, we measured county-level population changes, and based on this, constructed a panel dataset for 1747 counties from 2011 to 2020. Based on the push-pull theory and the Harris-Todaro model, this paper applied a time-varying difference-in-differences (DID) method to assess the impact of the E-commerce into the Rural Comprehensive Demonstration Counties (ERCDC) policy on local population migration and explored its potential mechanisms. Our findings indicate that: (1) The ERCDC policy has effectively reduced rural population outflow in pilot areas. (2) A range of robustness tests, including spillover effect testing, instrumental variable methods, and PSM-DID, confirm the robustness of the baseline results. (3) The policy effects are more pronounced in regions where government support for the digital economy is strong, market proximity is closer, public attention to digitalization is high, and the convenience of freight transportation is greater. (4) The ERCDC policy has significantly enhanced ‘income pull’, ‘employment pull’, and ‘entrepreneurship pull’ in pilot areas by increasing local income, improving local employment opportunities, and stimulating local entrepreneurship, thereby mitigating population outflow in these areas. This paper highlights the effectiveness of the digital economy in addressing rural population outflow in China, thereby providing important policy implications for governments in developing countries to address rural population challenges.

Inequality and climate change are major challenges for sustainable development, but a dilemma between the objectives has been widely observed. Based on the panel data of China Household Finance Survey (CHFS), inequality in carbon emissions across income groups is witnessed, which provides basics for the study. From a quasi-natural experiment, an increase of 9.9% in household per capita carbon emissions (HCEs) of the impoverished group is found after the Targeted Poverty Alleviation policies (TPA) in China, providing evidence for the enhancement of poverty alleviation measures on equal right for household carbon emissions. Specifically, dual mechanism of transfer payments and employment assistance acting as direct and indirect strategies to enhance family wealth are examined as the pathways to carbon equality. Further, a decline in household carbon emission intensity in the impoverished group is also observed after the treatment, which implies the accelerating role of TPA in low-carbon lifestyle formulation for the impoverished families. The findings of this paper confirm the positive effect of TPA policies on carbon equality for households, and also refute the "equality-pollution dilemma", which provide insights for policy makers in formulating equitable decarbonization policies and allocating the carbon budget.

Eliminating poverty and combating climate change are the twin pillars of global sustainable development. Investigating the relationship between poverty alleviation and carbon emissions reduction can provide valuable insights for global poverty governance and climate action. This study treats China's national-level povertystricken counties (NPC) policy as a quasi-natural experiment, adopting the difference-in-differences approach to explore the effects and influencing mechanisms of poverty alleviation policies on carbon emissions intensity using county panel data from 2010 to 2018. The empirical findings reveal that the NPC policy notably lowered local carbon emissions intensity by a remarkable 9.12%, generating environmental benefits of 20.2-121.2 billion yuan. Mechanism analysis demonstrates that the NPC policy contributed to poor counties' green development by promoting industrial upgrading and improving ecological restoration. Heterogeneity analysis reveals that the carbon emissions reduction effect of the NPC policy was more pronounced in counties with large populations and rich resource endowment. Finally, the study proposes practical recommendations to advance the low-carbon effects of economic support policies.

Using a unique dataset on the performance of soccer players in China (retrieved from 632 matches involving 24 teams during the 2014 to 2016 seasons), we investigate the effect of air pollution on different performance indicators that rely on different mixtures of the physical and cognitive inputs of players. To ensure a causal interpretation, we implement an instrumental variable (IV) approach using thermal inversion as the instrument for air pollution. We found that players’ performance indicators, especially those more related to cognitive factors, are more strongly influenced by air pollution. One standard deviation (SD) increase in the Air Quality Index (AQI) leads to 2.5% decrease in the number of players’ passes and 5.1% increase in the number of fouls. However, for performance indicators that are more related to players’ physical condition, e.g., running distances, no such significant impact is identified. Overall, these findings suggest that the negative impact of short-term air pollution exposure on outdoor worker performance is mainly cognitive, which we believe could lead to important policy implications, not only for competitive sports but also across a much broader spectrum of business sectors.

PurposeIn the process of making agricultural production decisions in rural households, severe weather conditions, either extreme cold or heat, may squeeze the labor input in the agricultural sector, leading to a reallocation of labor between the agricultural and non-agricultural sectors. By applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, reveal the mechanism of farmers' adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.Design/methodology/approachThis study utilizes data from Chinese meteorological stations and two waves of China Household Income Project to examine the impact and behavioral mechanism of extreme temperatures on rural labor reallocation.Findings(1) Extremely high and low temperatures had led to a reallocation of labor force from agricultural activities to non-farm employment, with a more pronounced effect from extreme high temperature events. (2) Extreme temperatures influence famers' decision in abandoning farmland and reducing investment in agricultural machinery, thus creating an interconnected impact on labor mobility. (3) The reallocation effect of rural labor induced by extreme temperatures is particularly evident for males, persons that perceives economic hardship or labor in economically active areas.Originality/valueBy applying a dataset with a wide latitude range, this study empirically confirms the influence of extreme temperatures on the agricultural labor reallocation, and reveals the mechanism of farmers' adaptive behavioral decision and therefore enriches the research on the impact of climate change on rural labor markets and livelihood strategies.

Promoting the intelligent transformation and green development in manufacturing is a vital part of building a modern industrial system. Therefore, the role of intelligent manufacturing in promoting the green development of firms is worthy of in-depth study. This paper takes the implementation of intelligent manufacturing pilot demonstration projects (IMDP) in China as a quasi-natural experiment, and manually sorts out the list companies with IMDP. The difference-in-difference method is adopted to investigate the effect of intelligent manufacturing on the corporate environmental performance. Empirical results reveal that intelligent manufacturing has noticeable improved the corporate environmental performance through increasing investment in environmental protection, expanding human capital and innovating green technology. This confirms the “green dividends” in enterprise intelligent transformation does exist. Further analysis shows that the “green dividends” brought by intelligent manufacturing is more pronounced in non-state-owned, capital market concerned, and large-scale enterprises. This study theoretically reveals the relationship between intelligent transformation and manufacturing's green development, and provides practical guidance for the promotion of national industrial intelligent policy, which enlightens the high-quality development of manufacturing in emerging economies.

Using a unique dataset on the performance of soccer players in China (retrieved from 632 matches involving 24 teams during the 2014 to 2016 seasons), we investigate the effect of air pollution on different performance indicators that rely on different mixtures of the physical and cognitive inputs of players. To ensure a causal interpretation, we implement an instrumental variable (IV) approach using thermal inversion as the instrument for air pollution. We found that players’ performance indicators, especially those more related to cognitive factors, are more strongly influenced by air pollution. One standard deviation (SD) increase in the Air Quality Index (AQI) leads to 2.5% decrease in the number of players’ passes and 5.1% increase in the number of fouls. However, for performance indicators that are more related to players’ physical condition, e.g., running distances, no such significant impact is identified. Overall, these findings suggest that the negative impact of short-term air pollution exposure on outdoor worker performance is mainly cognitive, which we believe could lead to important policy implications, not only for competitive sports but also across a much broader spectrum of business sectors.

Green manufacturing and corporate ESG performance are two vital issues related to sustainable development. Utilizing manually collated data of green factory, publicly listed company data and corporate ESG scores disclosed by the Bloomberg database, this paper adopts a difference-in-difference approach to explore the impact of green manufacturing on corporate ESG performance. The empirical results demonstrate that green manufacturing significantly enhances corporate ESG performance by expanding green investment and alleviating financing constraints. Further analysis indicates that green manufacturing plays a more crucial role in improving corporate environmental performance and social responsibility. The findings offer valuable insights for refining government environmental regulatory tools and for corporations aiming to enhance their ESG performance.

This paper examines the industrial chain ripple effect of ESG in upstream and downstream companies from the perspective of the entire industrial chain, utilizing data from Chinese A-share listed companies. The study reveals that the ESG performance of upstream and downstream companies significantly enhances the ESG performance of midstream focal companies within the industrial chain. The ripple effects of industrial chain ESG are more pronounced when the focal firm demonstrates financial stability, maintains geographic proximity to the upstream and downstream chains, possesses a larger firm size, or operates under private ownership. Further, the paper finds that corporate ESG initiatives exert industrial chain ripple effects through two channels: optimizing the matching of supply and demand between upstream and downstream companies and focal firms; and stabilizing the supply-demand relationship through interactions between focal firms and upstream and downstream entities. This study aims to elucidate the phenomenon of focal firms adopting ESG practices, and how it is affected by upstream and downstream entities within the industrial chain. It offers a novel perspective for fortifying the resilience of industrial chains against market uncertainties and disruption risks, thereby advancing the sustainable development of these chains.

Green Manufacturing, a pivotal aspect of green transformation, carries high expectations for its potential role in wealth creation and equitable distribution. This paper investigates whether the growth dividend resulting from Green Manufacturing benefits workers. Leveraging the “Green Factory” list released in 2017 and subsequent years as a quasi-natural experiment, we apply a time-varying difference-in-differences methodology to analyze the income distribution effects of Green Manufacturing. Our findings reveal that Green Manufacturing significantly boosts labor productivity within companies but does not notably impact worker wages, leading to a decline in the labor income share. Furthermore, we show that alleviating financing constraints and fostering green innovation are two prominent operating mechanisms, while human capital upgrading shows negligible effects. Overall, the evidence suggests that the growth dividends stemming from Green Manufacturing do not evenly benefit all input factors.

Faced with a surge in labour costs, companies are strongly incentivised by local governments’ aggressive promotion to embrace robotic technology, triggering intense media debates. This, in turn, inevitably shapes workers’ attitudes towards their current jobs and brings uncertainty about their future workplace. This study investigates the connection between robotisation, routinisation and job satisfaction in China’s labour market. The results show that there is an observed positive relationship between an individual’s job satisfaction and exposure to robots in the local labour market, which may be related to the overwhelming benefits of these new technologies about certain work dimensions. However, fear of automation is not groundless. Our findings show that job satisfaction decreased with an increase in the routinisation of task content, particularly in areas that are increasingly exposed to robot adoption. This supports the routine-biased technological change hypothesis, which connects technology-induced unemployment with job routinisation. JEL Classification: J28, O33

The automatic production line will alter the workflow and workshop production system, which will significantly impact how the workers perform their jobs. Using an employer-employee matching survey data from the manufacturing sector in Guangdong Province, this paper found that production automation upgrades significantly increase working hours. The findings remain robust even after dealing with endogeneity issues. A plausible explanation is that improved general-purpose technology integrated into the production system will damage employees' unique talents by "deskilling". The heterogeneity analysis shows that labor degradation caused by technological change can be effectively mitigated by labor union protection and accumulation of workers' human capital. Furthermore, production automation upgrades will probably change the way wages are paid, with less use of the piece-rate system. Although workers may receive some wage compensation for overwork, production automation upgrades may have unfavorable consequences (such as mental health, etc.). This study sheds light on how shop floor workers perform their jobs in the face of the wave of automation, offering fresh policy insights for promoting decent work and achieving inclusive growth.

The vigorous development of the digital economy will reshape labour demand, which in turn will affect the workplace choice of migrant workers and then their location. Taking the large-scale and highly-mobile immigrant workers in urban China as the research population, this paper conducted an empirical research on the impact of the digital economy on labour location using the data from the China Labour-force Dynamic Survey (2012-2016). Results show that the more developed a city's digital economy is, the more immigrants the city can attract and absorb. Analysis of the impact channels shows that the attraction of the digital economy to immigrants stems mainly from entrepreneurial opportunity provision and skill utilization enhancement effects. There is individual heterogeneity in the impact of the digital economy, with low-skilled, rural, or high communication ability migrant workers likely to be positively impacted by the development of the urban digital economy. While local governments are committed to digital technology-driven economic transformation, they should nonetheless promote the training of workers in the new era to achieve a better match between digital development and labour market.

Currently, data is increasingly becoming a crucial production factor and strategic resource for economic development. However, there is no consensus on whether data plays a significant role in promoting city green development. This paper examines the effect and the mechanism of big data on carbon emission reduction based on a quasi-natural experiment of Big Data Comprehensive Pilot Zones (BDCPZ) in China, using a difference-in-difference approach and combining panel data from 261 cities in China from 2010 to 2019. The study found that: (1) The policy of BDCPZ significantly reduced carbon emissions, which confirms the critical importance of the digital dividend in China's green development process. (2) We find the emission reduction effect of BDCPZ is achieved in three main ways: promoting industrial upgrading, improving energy use efficiency and increasing green TFP in manufacturing. (3) Further analysis reveals that the carbon emission reduction effect of BDCPZ varies depending on city population size, levels of manufacturing development, resource endowments, and pilot cities with low carbon related policies. This paper empirically confirms the digital dividend in city green transformation, provides evidence and policy guidance for the broad application of the digital economy in the field of green and low-carbon development, and enriches research in development economics and environmental economics. It helps to provide novel policy insights for the government to implement proactive policies of carbon reduction, and to build a diversified carbon reduction governance system to successfully achieve “carbon peak” and “carbon neutral” targets.